Des FitzGerald

Stochastic temperature, heat flow and geothermal gradient modeling direct from a 3D map of the Cooper Basin region, Central Australia

Significant volumes of Big Lake Suite granodiorite intrude basement in the Cooper Basin region of central Australia. Thick sedimentary sequences in the Cooper and overlying Eromanga Basins provide a thermal blanketing effect resulting in elevated temperatures at depth. 3D geological maps over the region have been produced from geologically constrained 3D inversions of gravity data. The inverted density models delineate regions of low density within the basement that are interpreted to be granitic bodies. The 3D maps include potential heat sources and thermally insulating cover, the key elements in generating an Enhanced Geothermal System (EGS) play. A region was extracted from the 3D geological map and used as a test-bed for modelling the temperature, heat flow and geothermal gradients. The test region was populated with thermal properties and boundary conditions were approximated. Temperatures were generated on a discretised version of the model within GeoModeller and were solved by explicit finite difference approximation using a Gauss-Seidel iterative scheme. The thermal properties that matched existing bottom hole temperatures and heat flows measurements were applied to the larger 3D map region. An enhancement of the GeoModeller software is to allow the input thermal properties to be specified as distribution functions. Multiple thermal simulations are carried out from the supplied distributions. Statistical methods are used to yield the probability estimates of the temperature and heat flow, reducing the risk of exploring for heat.

Automatic Modelling And Inversion For Dykes From Magnetic Tensor Gradient Profiles - Recent Progress

We have developed an optimization method for automatic dyke delineation from observed magnetic and gravity gradient traverse data. A non-linear least squares algorithm is used to find model dyke parameters that best fit the computed gradient tensor data to the observed data. The eigen-system of the observed magnetic gradient tensor data is used to provide starting model dyke parameters for an iterative non-linear least squares solver. This greatly enhances the ability of the solver to find a plausible dyke model for matching observed and synthetic tensor gradients locally. The method works well on synthetic examples. Multiple surveys using a Full Tensor Magnetic Gradient (FTMG) signal instrument from IPHT, have been made in Southern Africa. A real case study with remanence, taken from the Platreef near Pretoria, shows that the gross observed gradient features can be recovered by our procedure, but the residuals in the gradient fit hint strongly at the need for more complex dyke models. There is more directly inferable structural geology in this tensor signal than can be found in a conventional TMI signal.